The present invention relates generally to the field of pharmacogenomics and in particular to the use of biomarkers for identifying patients suitable for treatment as well as to methods of following their response to methods of treatment.
An effort to understand an individual patient's response or disease progression is the topic of present day research. Indeed, the field of pharmacogenomics or pharmacogenetics utilizes genomic data, pharmacology, and medicine, and often relies on advanced research tools to correlate genetic variability to one or more of predisposition to a disease and/or its progression, as well as therapeutic response to a drug or therapeutic regimen. Typically, multiple genes are analyzed simultaneously in a large-scale, genome-wide approach.
Proliferative cell disorders such as cancers usually develop through the accumulation of a series of mutations in the patient's DNA within a subpopulation of cells. These mutations may confer a survival advantage on the cells that causes them to grow and spread in an uncontrolled manner that is deleterious to the surrounding tissues. The particular set of mutations may be unique to an individual patient's tumor. Cancers of the same tissue or organ in different individuals may have originated from different sets of mutations, though certain mutations may be prevalent among particular cancer types. The characteristic set of mutations will determine how the cancer cells behave, and in particular, their likelihood of response to a given therapeutic regimen.
One may characterize the genetic alterations in a tumor by using advanced research tools that measure the genetic sequence of the tumor's DNA, or the RNA or proteins that are the expression of the altered DNA. It is a goal of current research to identify characteristics of an individual's tumor that are predictive of the likelihood of that tumor's response to various therapeutic treatments. Thus, one or more genes would be identified where presence of particular genetic mutations in the DNA, or their levels of expression, either as RNA transcripts or as proteins, or a combination of these factors, would be predictive of the likelihood that a particular treatment would affect the tumor in a manner that would be beneficial to the patient.
One main purpose is to determine which variations in individuals or subpopulations, associated with their genetics or the genetic characteristics of their disease, factor into drug efficacy and to create suitable tests, including diagnostic tests. Drugs that are tailored for patients with a particular genetic sequence, or for diseases characterized by particular genetic alterations, may thus be produced. The tests may also be used to guide treatment decisions, such as which drug or drug combination is mostly likely to be beneficial to the patient, and what dosing and schedule is most appropriate. Diagnostic tests and genetic profiling will help avoid the expense and the potentially detrimental trial-and-error approach to the suitability of a particular treatment regimen or a particular dosage level.
While the era of customized drugs may be coming, methods that utilize genetic information to identify specific individuals or subgroups for a particular type of treatment or optimization of a treatment may be immediately put to use today.
An individual's response to a particular treatment or predisposition to disease and the correlation to a particular gene of interest has been documented. It is now believed that cancer chemotherapy is limited by the predisposition of specific populations to drug toxicity or poor drug response. For a review of the use of germline polymorphisms in clinical oncology, see Lenz, H.-J. (2004) J. Clin. Oncol. 22(13):2519-2521. For a review of pharmacogenetic and pharmacogenomics in therapeutic antibody development for the treatment of cancer, see Yan and Beckman (2005) Biotechniques 39:565-568.
Results from numerous studies suggest several genes may play a major role in the principal pathways of cancer progression and recurrence, and that the corresponding germ-line polymorphisms may lead to significant differences at transcriptional and/or translational levels. Polymorphism has been linked to cancer susceptibility (oncogenes, tumor suppressor genes, and genes of enzymes involved in metabolic pathways) of individuals. In patients younger than 35 years, several markers for increased cancer risk have been identified. Cytochrome P4501A1 and gluthathione S-transferase M1 genotypes influence the risk of developing prostate cancer in younger patients. Similarly, mutations in the tumor suppressor gene, p53, are associated with brain tumors in young adults.
This approach may be extended to mutations that are specific to cancer cells, and not otherwise found in the patient's genome. For instance, it has been demonstrated clinically in patients with gastrointestinal stromal tumors (GIST) treated with the drug Gleevec (imatinib mesylate; Novartis) that particular activating mutations in the genes KIT and PDGFA are linked to higher response rates to the drug, see J Clin Oncol. 2003 Dec. 1; 21(23):4342-9.
By measuring changes in gene expression of cancer cell lines induced by treatment with a particular therapeutic agent, one may characterize the cells' response to that agent. This approach provides insight into the mechanism of the drug, including what biological processes or pathways it impacts. Such information can help guide the treatment of patients, by providing expectations as to which genes will change in response to treatment. An assay of those genes from a sample collected from a patient post-treatment could then be used to determine whether the drug was having the intended effect, and by extension, whether the dose or schedule should be altered, or the regimen discontinued. This approach would improve efficacy by ensuring that patients receive the most appropriate treatment.